1 Introduction

Some quantites about the data:

## dim(person) = 2000 62
## dim(sequences_meta) = 1000 41
## Are 'person' IDs unique ?
##  TRUE
## Are 'sequences_meta' IDs unique ?
##  TRUE
## The proportion of US-born people in the dataset is:
##         Foreign    USA
## Count     372.0 1628.0
## Percent    18.6   81.4
## The proportion of infected people after 2013 is:
##         Before 2013 (included) After 2013
## Count                   1802.0      198.0
## Percent                   90.1        9.9

2 Epidemiology: Washington State

Below, we focus on HIV infected individuals who are either:

  • currently living in Washington State,
  • lived in Washington State during HIV diagnosis or
  • lived in Washington State during AIDS diagnosis.
## Frequency: 84.7 % of the dataset.
## Count: 1694
## King County Frequency in Washington State: 70.84 %

2.1 HIV epidemic over time

The plot below shows new diagnosis every two years in Washington State.

Mainly, we notice that new diagnosis in MSM population decreases over the time. Nevertheless, the foreign MSM population increases until 07-08 and it stays constant until now. Next, the heterosexual population slightly decreases and again the foreign subpopulation seems to increase.

Number of people diagnosed with HIV, adjusting for reported deaths.

Number of people diagnosed with HIV, adjusting for reported deaths.

Last five years: Transmissions by ethnicity and origin.

Percent of alived people with HIV by county. Only most represented counties are considered.

2.2 Counties map

2.2.1 Infected people by county

Birth country.

Number of people living with HIV and registered by county.

Number of people living with HIV and registered by county.

Number of diagnosis in last five years.

2.2.2 Spatial distribution of new diagnosis in last five years by risk group.

Percent of MSM diagnosis the last five years by county.

Percent of IDU diagnosis in last five years by county.

Percent of US HSX diagnosis in last five years by county.

Percent of foreign-born HSX diagnosis in last five years by county.

2.3 Age at diagnosis

## Proportions of transmissions: 
##  Main  transmission: 98.47% 
##  Other transmission: 1.53%

Age at HIV diagnosis.

## Warning: Removed 6 rows containing non-finite values (stat_ydensity).
## Warning: Removed 6 rows containing non-finite values (stat_boxplot).

Age at HIV diagnosis in last five years.

2.4 ART

2.4.1 Years of starting ART

Year of first ART.

2.4.2 Time for starting ART after diagnosis

Time for starting ART after diagnosis.

2.4.3 The last five years

Only about the person infected the last five years.

Frequency of people starting ART by origin and ethinicity.

Frequency of people starting ART by age and sexual orientation.

Cumulative proportion of individuals from King County who started ART, by tranmission and for diagnosis in last five years.

Cumulative proportion of individuals from King County who started ART, by ethnicity and for diagnosis in last five years.

Cumulative proportion of individuals from King County who started ART, by age and for diagnosis in last five years.

Cumulative proportion of individuals from Washington State who started ART, by county and for diagnosis in last five years.

Cumulative proportion of individuals from Washington State who started ART, by diagnosis year and for diagnosis in last five years.

3 Epidemiology: King County

In this Section we consider persons for who King County is the:

  • residence at HIV diagnosis or
  • residence at AIDS diagnosis or
  • current residence.
## Frequency: 60 % of the dataset.
## Count: 1200

3.1 HIV epidemic over time

Number of new diagnosis every two years in King County.

Number of new diagnosis every two years in the other counties of Washington State.

## There are not non-KC cases in this dataset.

Number of people diagnosed with HIV, adjusting for reported deaths.

Number of people diagnosed with HIV, adjusting for reported deaths.

Last five years: Transmissions by ethnicity and origin.

Percent of alived people with HIV by county. Only most represented counties are considered.

3.2 Age at diagnosis

## Proportions of transmissions: 
##  Main  transmission: 98.67% 
##  Other transmission: 1.33%

Age at HIV diagnosis for US born people.

## Warning: Removed 5 rows containing non-finite values (stat_ydensity).
## Warning: Removed 5 rows containing non-finite values (stat_boxplot).

Age at HIV diagnosis for migrants.

## Warning: Removed 5 rows containing non-finite values (stat_ydensity).
## Warning: Removed 5 rows containing non-finite values (stat_boxplot).

Age at HIV diagnosis in last five years.

3.3 ART

3.3.1 Years of starting ART

Year of first ART.

3.3.2 Time for starting ART after diagnosis

Time for starting ART after diagnosis.

3.3.3 The last five years

Only about the person infected the last five years.

Frequency of people starting ART by origin and ethinicity.

Frequency of people starting ART by age and sexual orientation.

4 Viral RNA sequences

In this section, we investigate who are the people whose viral RNA sequence we have.

## The viral RNA sequence file contains 100% about the PR/RT region.
## Count: 1000

4.1 Sequencing Map

Number of sequenced person by county in the US.

Percent of sequenced person by county.

Percent of sequenced person infected the last five years by county.

4.2 Sequencing distributions

Sequenced persons by birth country.

Sequenced persons by ethnicity and origin. (does not work on example data)

Sequenced persons by transmission and origin.

Sequenced persons by age and origin.

Sequenced persons by ART.

4.3 Evolution of sequencing

Evolution of sequencing by trasnmission.

Evolution of sequencing by ethnicity.

5 Outside Washington State

Below we study persons who have never been registered in Washington State and who are still in the dataset.

## The proportion of US born is:
##         Foreign    USA
## Count     68.00 238.00
## Percent   22.22  77.78

Current county.

Last five years: Transmissions by ethnicity and origin.

Number of alived people with HIV

6 Other plots

Below, the plots give information about the CD4 and VL counts.

6.1 For all the sample

CD4 count distributions in fonction of time between diagnosis and count.

VL count distributions in fonction of time between diagnosis and count.

CD4 count distributions in fonction of time between diagnosis and count. (with a zoom to drop extreme values.)

6.2 Concerning US-born people

CD4 and VL counts distributions for US-born people in fonction of time between diagnosis and count.

6.3 Concerning migrants

CD4 and VL counts distributions for migrants in fonction of time between diagnosis and count.

6.4 VL count after HIV diagnosis

Below, the plot give information about people who have a VL count greater than 200 after HIV diagnosis.

Frequency of ethnicity for these people by age.

Frequency of ethnicity for these people in function of the time between HIV diagnosis and the VL count.

Frequency of these people starting ART in function of the time between HIV diagnosis and the VL count.